1. Field of the Invention
The present invention relates to an image processing method, and more particularly, to an image processing method that prevents deviation from a lane by a vehicle.
2. Description of the Related Art
Various technologies are continuously being developed to improve the safety and convenience of vehicles. One such technology is a system for preventing the inadvertent deviation from a lane, which, in the case of inadvertent deviation from the lane as a result of driver carelessness, drowsiness, etc., either warns the driver or performs control to correct the positioning of the vehicle. In more detail, the lane deviation prevention system determines the location of the lane markers defining the lane the vehicle is traveling in, then determines the location of the vehicle relative to the lane markers. If the vehicle is deviating from the lane, either the driver is warned or a steering actuator is operated to make corrections to the position of the vehicle.
The main elements of a vehicle lane deviation prevention system (that provides steering control) are a photographing unit for obtaining photographs of the road on which a vehicle is traveling, an image processor for extracting from the photographs positions of the lane markers and of the vehicle relative to the lane markers, a steering controller for generating instructions as needed to make corrections in the position of the vehicle, and a steering actuator that is driven to adjust the steering of the vehicle according to the steering instructions generated by the steering controller.
In a conventional image processing method for a lane deviation prevention system, algorithms based on edges of the images are used to process the photographed images, thereby extracting the lane markers defining the lane. With this method, it is difficult to find ways in which to cope with the noise in the image data. Also, a substantial amount of time is used in image processing.
In addition to the image processing methods in which edges of the images are used, there is disclosed a method in which a gray level of images is used to extract lane markers. However, this method is error prone and performance easily varies with changes in the brightness of the images. That is, objects in the road may be mistaken for lane markers, and vehicle lane extraction proves difficult at night, on cloudy days, or when a peripheral brightness is low.
There is also a method in which color processing of images is performed. However, the camera and other equipment required are expensive with the application of this method, and the processing method is complicated such that processing times are increased.